Noviscient, a Singapore-based alternative investment shop, is crowdsourcing independent systematic traders and packaging them into a hedge fund.

The aim is to use APIs and a computerized risk model to create a vehicle that strips out almost all of the costs associated with hedge funds, while providing a business opportunity for quants with clever ideas.

“I’m not paying portfolio managers,” said Scott Treloar, founder. “They only get paid if they perform.”

He says Noviscient is not a matching service: it’s a “platform fund”. He’s not putting fund managers together with institutional investors. “The value is in selecting who has got alpha,” he told DigFin. “We allocate to managers doing well and weed out those doing poorly.”

There is plenty of talent out there, people coming out of investment banks or other funds who want to apply their quant expertise to portfolios, but the high capital requirements to start a hedge fund tend to strangle most of these efforts.

The bleeding edge

Noviscient, therefore, despite being tiny and brand new (its first fund launched in April), is trying to inject some new thinking into an industry that, in Asia, has been struggling.

Since the 2008 financial crisis, it has become very difficult for Asia-based hedge funds to raise substantial capital, especially amid soaring costs (for compliance, plus the platform and service required to cater to institutional investors). Nor is there much support from the region’s own institutions, which tend to invest in large, brand-name firms from the U.S.

Worse: few Asian funds have delivered the risk-adjusted returns to stand out, even in local strategies. “Performance has been pedestrian,” said Stephen Diggle, founder of Singapore-based Vulpes Investment Management. Vulpes is a business that evolved out of Diggle’s hedge fund, Artradis Fund Management, which scaled to $4.8 billion in 2008, after which point he returned most investor money.

Crowdsourcing strategies

Treloar previously worked at Vulpes, first as a quant manager, and then to help Diggle set up Kit Trading Fund, a multi-strategy hedge fund based on a similar idea to Noviscient’s: crowdsourcing clever managers to run both their own money and some of Vulpes’s. But whereas Kit involves traditional human-based strategies, Noviscient is dedicated to statistical-arbitrage ideas, trading in liquid exchange-listed products, that are driven by machines.

“We prefer faster trading strategies,” Treloar said, “because the higher the turnover, the more the machine can understand it.”

It is not a high-frequency or market-making fund. Nor is it a smart-beta product. Its performance comes from the machine’s portfolio construction as much as the underlying risk exposures. And it likes to work with external managers that understand new sets of alternative data that can determine price discrepancies ahead of earnings announcements and other set-piece corporate activities.

Can Noviscient make an impact in the industry? Diggle says Kit Trading Fund has won negligible AUM over the past two years.

But if Noviscient can prove its performance – in a live environment, not using backtested data – and keep its costs extremely low, the startup might gradually convince investors that it’s not going to disappear.

“He [Treloar] will need people to make a leap of faith that the business can carry on,” Diggle said.

If Noviscient can achieve that, Diggle welcomes its entry as a shot in the arm for Asian hedge funds. “The Asian hedge-fund universe is lacking dynamism right now…it needs some juice, to get flows moving again.”

Eat what you kill

Treloar says systematic traders from anywhere in the world send signals to Noviscient via APIs. Noviscient uses its proprietary algos to size them, decide whether to trade them, and allocate capital to them, a balance that the computer is constantly adjusting. “We use machine learning statistics to model the strategies,” he said. “We have a probability of alpha in each signal.”

Noviscient will not charge investors a management fee. Instead it will charge them a 36% performance fee, provided it meets its high-water marks (i.e., minimum performance levels). Of that, 20% goes back to those managers that meet their own performance targets. The fund offers monthly liquidity to investors.

The company doesn’t have rent other than desks at a Singapore co-working space; it doesn’t pay salaries for portfolio managers; its infrastructure is AWS’s cloud service. Its staff are paid a low base with a profit share. This means the business can scale either up or down, depending on fund flows, without disruption.

As it scales, it will have to pay for fund administration and, if it gets big enough, prime brokerage. For now, Saxo Bank is providing a basic version of those services.

But that could take a while.

“Right now we’re working to prove the concept,” he said. Treloar reckons institutions will struggle to categorize Noviscient, which means it may need to go a long time before it attracts substantial capital.

“We’re not a multi-strat or a fund-of-funds or a fintech,” Treloar said. “We’re about machine learning, cloud computing, A.I., and a shift to independent work: all of which the traditional funds industry is resisting. So we’re just going to be at the bleeding edge and suffer – but we’re low cost and aligned with our customers.”